ACDC Lab
Advanced Cross-media Data Computing Group
Cross-media Data Computing Β· Explore Intelligence, Connect the World
Focusing on social media & data mining, AI applications, multimodal learning and large models, we are dedicated to data-driven intelligent computing and applied innovation.
About the Group
GROUP INTRODUCTION
The ACDC group is led by Prof. Jinpeng Chen, Associate Professor and Doctoral Advisor at the School of Computer Science (National Model Software College), Beijing University of Posts and Telecommunications (BUPT), and Deputy Director of the Digital & Intelligent Transformation Department. His research interests include data mining & intelligent computing, AI & applications, and multimodal learning. He has led or participated in 40+ national, provincial/ministerial, and industry research projects, published 100+ papers at leading venues such as SIGIR, WWW, NeurIPS, ICML, AAAI, ACM MM, ACL, EMNLP, TKDE, and TMC, and holds 14 granted/pending patents.
He received the ICONIP 2022 Best Paper Award, the Zhou Jiongpan Outstanding Young Teacher Award, and the "Beijing Mobile" Teaching Innovation Award, among others. He serves on the CAAI Intelligent Service Technical Committee and the CIPS Social Media Processing & Language and Knowledge Computing Technical Committees, and as an early-career editorial board member of Big Data Mining and Analytics, executive committee member of Computer Science, and assistant editor of the Journal of Intelligent Systems.
Welcome to the ACDC Family
Our research currently focuses on recommender systems / model lightweighting / autonomous driving. We welcome collaborators in related directions; interested students are invited to send your CV to jpchen [at] bupt [dot] edu [dot] cn.
Computing resources: the group maintains dedicated compute resources and also rents substantial AutoDL capacity for model training.
Research Directions
MAIN RESEARCH
Recommender Systems
Personalized recommendation over large-scale data, including retrieval, ranking, diversity, and explainability.
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Multimodal Learning
Representation learning and fusion modeling of text, image, video, and audio for cross-modal understanding and generation.
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Multi-Agent Learning
Multi-agent collaboration and game theory, reinforcement learning and decision optimization for complex intelligent agent systems.
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JOIN US
Join ACDC and Create the Future Together
Work alongside talented peers, explore cutting-edge technology, solve real-world problems, and turn ideas into impact.